OTMol:通过最佳运输进行坚固分子结构比较
Xiaoqi Wei1, Xuhang Dai2, Yaqi Wu3
1Department of Mathematics, North Carolina State University, Raleigh, North Carolina 27695, United States.
Journal of chemical information and modeling
|October 8, 2025
概括
我们介绍了OTMol,一种使用最佳运输进行分子对齐的新方法. OTMol精确匹配原子,保持化学特征,如拉性,可靠的结构比较.
科学领域:
- 计算化学是一种计算化学.
- 结构生物信息学 结构生物信息学
- 机器学习在化学中的应用
背景情况:
- 根-平方平均偏差 (RMSD) 对于分子结构相似性评估至关重要.
- 传统的RMSD方法与原子排序,集群配置和奇拉性作斗争.
- 现有的对齐算法往往无法在各种化学系统中进行概括.
研究的目的:
- 开发一种强大且可通用的分子对齐方法.
- 克服传统RMSD计算的局限性,包括原子对应问题.
- 为了利用内在的分子信息进行准确的结构比较.
主要方法:
- 制定了分子对齐作为一个合监督的格罗莫夫-瓦瑟斯坦 (fsGW) 最佳运输问题.
- 利用分子内部的内在几何和拓关系进行数据驱动的匹配.
- 确保一对一的原子映射以保持分子完整性.
主要成果:
- 在ATP,伊马替尼,脂质,和水等多种系统中,OTMol实现了较低的RMSD值.
- 该方法保留了关键的化学特征,包括分子性和键连接性.
- OTMol证明了计算效率,并避免了集群中错误的多对一对齐.
结论:
- 最佳运输理论为分子对齐提供了一个强大的框架.
- OTMol提供了一个基于原则的,数据驱动的方法,优于启发式方法.
- 这种方法推进了化学信息学和分子建模中的结构比较.
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